Detection and Mitigation of Biasing Attacks on Distributed Estimation Networks

The paper considers a problem of detecting and mitigating biasing attacks on networks of state observers targeting cooperative state estimation algorithms. The problem is cast within the recently developed framework of distributed estimation utilizing the vector dissipativity approach. The paper shows that a network of distributed observers can be endowed with an additional attack detection layer capable of detecting biasing attacks and correcting their effect on estimates produced by the network. An example is provided to illustrate the performance of the proposed distributed attack detector.Comment: Accepted for publication in Automatic

A distributed finite-time observer for linear systems

International audienceIn this paper, the problem of distributed estimation for a linear large-scale system is studied. A nonlinear distributed observer is proposed, whose estimation error converges to zero in a finite time. A fixed-time converging version of the observer is also presented. The efficiency of estimators is demonstrated by computer simulations